Neoliberal smart cities cause deputization of economic zones and sectors to monopoly capital – creates unsustainable, predatory market strategies AND surveillance capitalism

[Evgeny and Frencesca, “RETHINKING THE SMART CITY: DEMOCRATIZING URBAN TECHNOLOGY,” Rosa Luxemberg Foundation, January 2018, , Accessed 7/2/23, GDS – PL]

Two such processes are of particular importance to our discussion: the delegation and subcontracting of responsibilities previously reserved to public institutions to private players, along with the enlistment of private financial capital—mostly from pension funds, insurance firms, various alternative asset management funds—into the management, maintenance, and construction of infrastructure, most of which operates at a local level. Both exhibit significant, albeit underexplored connections to the smart city agenda, as both require an extensive infrastructure of gathering, analyzing, and acting upon data to succeed and proliferate. Subcontracting can, of course, be described as a further privatization of public services— indeed, such a description would be entirely correct. While the exact service providers and distribution of responsibility between them and public institutions vary from country to country, we can nonetheless identify several similarities.

First, much of this subcontracting is facilitated by the so-called Big Four accounting and consulting firms (Ernst & Young, Deloitte, PwC, KPMG), many of which now double as technology providers, investing heavily in technologies like blockchain and Big Data. Some speak of the “solutions economy” (Deloitte), while others promise an “outcome economy” (Accenture). The end result, however, is the same: This model rests on the commodification of solutions to social and political problems, the enlistment of actors (like banks and other fi nancial institutions) which would traditionally not be part of the “solution,” and the intensive deployment of data analytics and measurement to assess whether specific targets or outcomes are being delivered, coupled with timely interventions to steer the process towards said outcomes. None of this would be possible without an extensive infrastructure for tracking and controlling both physical and human resources, with quantification of performance paving the way for all sorts of other, even more advanced experiments to be constructed on this foundation. The rapid proliferation of social impact bonds illustrates the operative logic of the hybrid “solutions” or “outcome” economy at play here. Such bonds are issued by governments as they delegate responsibility for a particular sector— such as prisons or schools—to financial firms like Goldman Sachs. The latter pledges to meet a particular target such as of repeated offenses in the case of prisons or literacy rates in the case of schools, and is only paid for its services if that target is met.

To encourage financial firms to participate in such endeavours, their risks are often underwritten by foundations, who, caught up in their own philanthrocapitalist bliss, would like to see the social sector become subservient to the logic of financialization. The practice is extremely controversial and several such experiments have already failed, but that should not detract us from grasping one important feature of what a successful social investment bond entails from the perspective of, say, Goldman Sachs: It requires the ability to monitor and extract the maximum amount of value from resources under management, which entails perpetual surveillance coupled with nudging and other forms of producing desired behavior. Moreover, should monitoring capacity prove insufficient, it would be advantageous to have the means to produce statistics so obscure and impenetrable that the operating entity—in this case, Goldman Sachs— can claim that it has in fact met its target and should be paid the amount due (as regularly happens in actual projects fi nanced through social investment bonds). Surrendering control over such statistical and computation capabilities—an inevitable consequence of the privatized smart city—is a sure way to be swindled by private service providers on a regular basis. The enlistment of financial capital into the provision of infrastructure operates according to a rather similar logic. Most industry players from asset management funds to private equity firms do not intend to hold the infrastructure they invest in for a long period of time; usually, they hope to make a large enough speculative gain and exit within a decade (although even if the speculative gain is not large enough, most such fi rms earn their money from transaction and management fees independent of returns).

The model’s obvious downside is chronic underinvestment into long-term facilities and planning of the infrastructure in question, as investors adopting a short-term perspective are not motivated to undertake expensive infrastructural upgrades. This is only part of the problem, however, as investors also seek to extract as much value from the asset under management in the short period of time they own it as possible, often degrading it much faster than a longer-term operator or owner would. This is known as “sweating the asset” in industry parlance—a typical practice among infrastructure investors. This occurs in several ways. One method is to charge users the highest bearable price, usually a rather high figure with infrastructure as most of these goods and assets are almost by definition scarce and do not have easy alternatives. Another method is to use the assets more heavily, ensuring they never lie dormant and increasing capacity utilization almost to the maximum. This may have been a difficult undertaking twenty or thirty years ago, but with today’s sensors and ubiquitous capability, finding alternative users for dormant infrastructure is as easy as finding tenants for an empty apartment on Airbnb.

In other words, “sweating the asset” presupposes the same smart infrastructure of sensors, connectivity, and basic computing as the outcome and solutions economy: Neoliberal techniques appear far less effective in the absence of technological infrastructure to activate and profit from them. The need to charge people different prices based on their ability and eagerness to pay also points to the importance of personal and reputational data in this model’s proliferation: As long as differentiated pricing remains the best way to maximize one’s revenue stream from an asset, we can rest assured that sensors—including highly advanced biometric sensors capable of identifying us and linking our faces to our social media accounts—will continue to invade our cities. To even try to explain the proliferation of assets and connectivity in the built environment without looking at the underlying political and economic drivers is thus a rather futile exercise. One can, of course, go on hoping that these sensors and routers will be deployed to humanize and personalize national and local bureaucracy—yet this seems like a rather naïve aspiration given that bureaucracy itself is increasingly being taken out of the government’s hands.

Once privatized, this humanizing rationale disappears as if it never existed: A privatized toll road—the quintessential example of smart infrastructure built to “sweat the asset”—has no need for humanism. Surprisingly, most traditional accounts of the rise of smart city ideology downplay the role of the most powerful sector in our cities, real estate and construction companies—if they mention it at all. In a way, their interest in “smartness” is similar to that of infrastructure investors: Sensors and connectivity allow for more hands-on management of their resources, including buildings, the structural faults, problems, and ineffi ciencies of which can now be identified, fixed, and predicted in real time. This transition to “smart buildings” and “smart assets” allows real estate firms to charge a “smartness” premium, thus driving up the already prohibitive costs of real estate.17 Once such buildings and assets proliferate, cities can market entire “smart districts”, accelerating the process of gentrification and driving rents even higher—especially if one can also demonstrate that the area is popular among local entrepreneurs and start-ups.

Tellingly, Richard Florida, the proselytizer-in-chief of the “creative class” and the requisite “start-up cities,” has now become the main cheerleader for “start-up districts,”18 drawing up (as one would expect) rankings of districts based on their “smartness” and “startuppiness.” Moreover, the proliferation of secondary data on tenants permits a more effective form of renter screening, reducing the risks of delayed payment and other costs associated with problematic tenants. Not surprisingly, several start-ups already off er such screening services, promising landlords and real estate fi rms risk profiles of potential tenants based on careful analysis of their online activity. In this instance, the logic of the gated community is applied not only to the outside but increasingly within: Credit scores and letters of reference no longer suffice, one must now work and produce the requisite online reputation to qualify to live in a particular “building.” This production of the complacent entrepreneurial ethos is very much in line with the overall project of reengineering the soul as advanced by neoliberalism.